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CLAD-Net: cross-layer aggregation attention network for real-time endoscopic instrument detection.

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第一作者： Xiushun,Zhao

第一单位： School of Automation, Guangdong University of Technology, Guangzhou, 510006 China.

作者： Xiushun,Zhao ^[1] ; Jing,Guo ^[1] ; Zhaoshui,He ^[1] ; Xiaobing,Jiang ^[2] ; Haifang,Lou ^[3] ; Depei,Li ^[2]

作者单位： School of Automation, Guangdong University of Technology, Guangzhou, 510006 China. ^[1] Department of Neurosurgery, Sun Yat-Sen University Cancer Center, Guangzhou, 510006 China. ^[2] Department of Gastroenterology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, 310006 China. ^[3]

关键词 Composite attention mechanism Cross-layer feature aggregation Refinement module Surgical instrument detection

DOI 10.1007/s13755-023-00260-9

PMID 38028959

发布时间 2024-12-02

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Health information science and systems

2023年11卷1期

58页

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Health information science and systems

2023年11卷1期

58页

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CLAD-Net: cross-layer aggregation attention network for real-time endoscopic instrument detection.

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CLAD-Net: cross-layer aggregation attention network for real-time endoscopic instrument detection.

Health information science and systems

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Health information science and systems

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